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03/15/2023
The Devil's Advocate: Shattering the Illusion of Unexploitable Data using Diffusion Models
Protecting personal data against the exploitation of machine learning mo...
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01/26/2023
Distilling Cognitive Backdoor Patterns within an Image
This paper proposes a simple method to distill and detect backdoor patte...
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10/13/2022
COLLIDER: A Robust Training Framework for Backdoor Data
Deep neural network (DNN) classifiers are vulnerable to backdoor attacks...
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09/13/2022
Adversarial Coreset Selection for Efficient Robust Training
Neural networks are vulnerable to adversarial attacks: adding well-craft...
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05/20/2022
Robust Task-Oriented Dialogue Generation with Contrastive Pre-training and Adversarial Filtering
Data artifacts incentivize machine learning models to learn non-transfer...
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12/01/2021
ℓ_∞-Robustness and Beyond: Unleashing Efficient Adversarial Training
Neural networks are vulnerable to adversarial attacks: adding well-craft...
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10/26/2021
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Bounding box (bbox) regression is a fundamental task in computer vision....
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09/23/2020
Segmented Pairwise Distance for Time Series with Large Discontinuities
Time series with large discontinuities are common in many scenarios. How...
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09/23/2020
Learning Non-Unique Segmentation with Reward-Penalty Dice Loss
Semantic segmentation is one of the key problems in the field of compute...
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08/02/2020
Detecting Relevant Feature Interactions for Recommender Systems via Graph Neural Networks
Feature interactions are essential for achieving high accuracy in recomm...
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07/15/2020
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
Deep learning classifiers are susceptible to well-crafted, imperceptible...
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07/06/2020
Black-box Adversarial Example Generation with Normalizing Flows
Deep neural network classifiers suffer from adversarial vulnerability: w...
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06/24/2020
Normalized Loss Functions for Deep Learning with Noisy Labels
Robust loss functions are essential for training accurate deep neural ne...
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03/25/2020
Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction
Predictive process monitoring aims to predict future characteristics of ...
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01/15/2020
Invertible Generative Modeling using Linear Rational Splines
Normalizing flows attempt to model an arbitrary probability distribution...
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02/25/2019
Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking
Recent studies have demonstrated that reinforcement learning (RL) agents...
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08/17/2018
